Detail

Keywords

Computational Modelling; Dynamical Systems; Machine Learning; Neurosciences; Robotics

Research group(s)

• Dynamics of Neural Systems Laboratory
  Head: Gosztolai Adam
  Research Area: We are motivated by two synergistic aims: 1. Developing novel methods using machine learning, geometry and dynamical systems theory for discovering better models of how the brain works, 2. Reverse-engineering the dynamical systems that underpin cognitive processes to develop more advanced AI systems that benefit clinical applications such as brain-machine interfaces.
  Members:
  Gosztolai Adam

Grants

• ERC Starting Grant (2024)
  Source of Funding: Medical University of Vienna, Horizon 2024
  Principal Investigator

Selected publications

1. Gosztolai, A. et al. (2024) ‘Interpretable statistical representations of neural population dynamics and geometry’. Nature Methods Available at: https://arxiv.org/abs/2304.03376.
2. Gosztolai, A. and Arnaudon, A. (2021) ‘Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature’, Nature Communications, 12(1). Available at: https://doi.org/10.1038/s41467-021-24884-1.
3. Gosztolai, A. et al. (2021) ‘LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals’, Nature Methods, 18(8), pp. 975–981. Available at: https://doi.org/10.1038/s41592-021-01226-z.